THE MICHAELANGELO LAB
THE MIBI TEAM
Mike Angelo, MD PhD
Principal Investigator
B.S. University of Mississippi
M.D. Ph.D. Duke University
Residency in Clinical Pathology, UCSF
mangelo0(at)stanford.edu
Mike's academic background spans across the fields of physics, biochemistry, electrical engineering, and medicine. During his residency he became interested in developing novel methods for immunohistochemical multiplexing using mass spectrometry leading to the development of MIBI during his postdoctoral work in the Nolan lab at Stanford University. Mike is now interested in optimizing MIBI and other mass reporter-based technologies further with the goal of identifying new transcriptional and translational signatures in solid tissue malignancies, and in allergic and other immunological disorders that can be used to improve clinical diagnosis and treatment
Staff
Marc Bosse, PhD
Senior Staff Scientist
B.Sc. Microbiology, University of Montreal
M.Sc. Microbiology & Immunology, University of Montreal
Ph.D. in Experimental Medicine, Laval University, Canada
Postdoctoral fellow, Robarts Research Institute | Postdoctoral Fellow, SCC-RI, McMaster University
Research Area: Instrumentation and assay development
mbosse(at)stanford.edu
Marc has broad experience in microbiology, human stem cell biology and asthma research. He also worked in translational research developing a production process for an advance cell therapy product. He now works closely with Drs. Angelo and Bendall on improving MIBI technology. He is responsible for the maintenance of the MIBI-TOF imager and its day-to-day operation. He is also engaged in the development and adaption of molecular techniques for MIBI.
Roshan Angoshtari, PhD
Staff Scientist
Ph.D. Genetics, Michigan State University
Research Area: Food allergy
r.angoshtari(at)stanford.edu
Alex Baranski
Computational Staff Scientist
B.S. Mathematics, University of Chicago
Research Area: Machine learning and computational analysis
Alex is interested in the theoretical study and practical development of artificial intelligence, and looks to biological systems such as the immune system as a source of inspiration for how to construct computational models that can adapt and self-organize. He works primarily on building machine learning tools for data analysis, and applying dynamical systems, information, and automata theory to building numerical simulations.
Christine Camacho
Life Science Technician I
B.S. Genetics, Molecular, & Cellular Biology, University of California, Davis
Research Area: QC development/optimization, research support
christinecamacho(at)stanford.edu
Christine has a broad range of research experience in industrial, academic and clinical lab settings, which most recently includes a study utilizing histology guided mass spectrometry to analyze proteomic expression in melanoma vs atypical benign nevi. Her focus in the lab is maintaining, processing, and conjugating all antibodies, developing/optimizing QC protocols, and developing a way to integrate MIBI as a QC tool for the lab. She also supports a project focused on developing tools for cell segmentation and annotates data used to train deep learning models. Her research interests include learning and utilizing computational tools to study expression in different cancers.
Postdoctoral Fellows
Leeat Keren, PhD
Postdoctoral Fellow, Damon Runyon Fellowship
B.Sc. Bioinformatics, Tel-Aviv University
M.Sc. Computational Biology, Weizmann Institute
Ph.D. Computational Biology, Wiezmann Institute
Research Area: Computational tool development and tumor-immune interactions
lkeren(at)stanford.edu
The immune system plays a critical role in modulating cancer progression. However, knowledge of the composition, phenotype, organization, and interactions between immune cells and tumor cells is limited. Leeat applies multiplexed imaging to study the interplay between the tumor and the immune system. She develops computational tools that allow to tease various layers of information from rich multiplexed-imaging data and employ them to infer design principles in tumor-immune interactions.
Tyler Risom, PhD
Postdoctoral Fellow, American Cancer Society Fellow
B.A. Molecular, Cellular Developmental Biology, University of Colorado
Ph.D. Cancer Biology, Oregon Health & Science University
Research Area: Ductal cell carcinoma in situ, melanoma, pancreatic cancer
trisom(at)stanford.edu
Tyler uses multiplexed imaging to profile the phenotypic content, phenotypic identity, and paracrine signaling between tumor and stromal cells in patient samples of ductal carcinoma in situ (DCIS) that did, or did not, recur with invasive breast carcinoma. This work will hopefully lead to the identification of biomarkers that can better risk stratify DCIS patients as well as identifying new molecular targets that could inhibit the progression of breast cancer to an invasive state.
Shirley Greenbaum, MD
Postdoctoral Fellow, Stanford SoM Dean's Fellowship
M.D. The Hebrew University of Jerusalem, Hadassah Medical School
Research Area: Placenta immunobiology
gshirley(at)stanford.edu
After completing her MD at the Hebrew University, Israel, Shirley joined the OBGYN residency program at Soroka University Hospital, of which she completed 3 years. Shirley then became very interested in research, particularly pregnancy complications related to the placenta and decided to take a time-off from clinical work to study the immunological interface between the mother and fetus.
Graduate Students
Erin McCaffrey
Graduate Student, Immunology, NSF Fellowship
B.S. Microbiology, University of Maryland-College Park
Research Area: Tuberculosis and granulomatous diseases
erinmcc(at)stanford.edu
During her undergraduate work in microbiology Erin became interested in the complex immune-evasion strategies of M. tuberculosis (TB) and its massive global burden in underserved patient populations. Her work focuses on elucidating immune mechanisms within TB granulomas that may drive disparate clinical outcomes. She is employing MIBI to identify immune cell populations, define their phenotypes, and asses their histologic organization within granulomas across the disease spectrum of TB in both human and non-human primate models of infection.
Noah Greenwald
Graduate Student, Cancer Biology, Stanford Graduate Fellowship
Co-Advisor: Dr. Christina Curtis
B.A. Biophysics, Harvard University
Research Area: Computational image analysis and cancer biology
nfgreen(at)stanford.edu
Noah received his BA in Biophysics from Harvard University. He then worked for two years at Harvard Medical School and the Broad Institute in the labs of Drs. Rameen Beroukhim and Ian Dunn studying the genomics of brain tumors. Noah is interested in combining multiplexed imaging techniques with genomics to understand the tumor microenvironment and response to therapy. He also works on developing tools for cell segmentation and computational analysis.
Alea Delmastro
Graduate Research Assistant, Biomedical Informatics
B.S. Chemical Engineering, Stanford University
M.S. Biomedical Informatics, Stanford University (anticipated 2021)
Research Area: Tuberculosis and granulomatous diseases
alead(at)stanford.edu
Alea is a graduate student in the Biomedical Informatics department. She is interested in studying infectious disease, specifically relating to Tuberculosis (TB) infection. Despite its large global burden, the human immune response to Mycobacterium tuberculosis remains poorly characterized. Utilizing multiplexed ion beam imaging and computational methods for single cell analyses, Alea aims to elucidate the composition and structure of TB granulomas in the Non-Human Primate model of both latent and active infection.
Candace Liu
Graduate Student, Immunology, Stanford Graduate Fellowship
B.S. Chemical & Biomolecular Engineering, Johns Hopkins University
Research Area: HIV, multi-omics integration and machine learning
cliu72(at)stanford.edu
After finishing her undergraduate degree at Johns Hopkins, Candace worked at the National Institutes of Health for two years in the Laboratory of Immune System Biology under Dr. John Tsang, where she became interested in systems immunology and computational biology. She is interested in combining MIBI with genomics and/or epigenomics data to study latent viral reservoirs in HIV infection. She is also interested in building machine learning tools for image analysis.
Erin Soon
Graduate Student, Immunology, National Science Scholarship, A*STAR
B.Sc. Pharmacology, Imperial College London
Research Area: Placenta immunobiology
erinsoon(at)stanford.edu
Erin first became interested in fetal immunology while working with Florent Ginhoux at the Singapore Immunology Network during her undergraduate days. She subsequently dabbled in translational immunotherapy for chronic wounds and zebrafish genetics before deciding that she wanted to return to exploring the immune interactions at play during pregnancy. She is leveraging MIBI and complementary single cell analyses to interrogate the mechanisms of immune tolerance at the maternal-fetal interface.
Ariane Blank
Graduate Student, Cancer Biology
B.S. in Biological Sciences, University of Chicago
Research Area: Tumor immunology
arianeb(at)stanford.edu
Ariane received her B.S. in Biological Sciences from the University of Chicago in 2018. During her undergraduate studies, Ariane contributed to research investigating the role of tissue resident macrophages in obesity-associated triple negative breast cancer and became interested in cancer immunology. In the Angelo lab, Ariane is leveraging CyTOF and MIBI to study the role of endogenous retrovirus proteins in mediating immunosuppression in a variety of cancer types.
Ke Leow
Graduate Student, Cancer Biology, National Science Scholarship, A*STAR
B.Sc. in Biochemistry, Imperial College London
Research Area: Post-translational modifications and cancer biology
kxleow(at)stanford.edu
Through her undergraduate studies in Imperial College London, Ke found strong interest in systems biology and omics technologies. She performed mass spectrometry analysis of glycans in human platelets during her final year project in Dr Anne Dell’s and Dr Stuart Haslam’s lab. Then, she worked for a year in the metabolomics group at Bioprocessing Technology Institute in Singapore. Ke is now interested in studying the effects of glycosylation on cancer immunotherapy using MIBI. She also hopes to develop tools for imaging glycoproteins.